Multi-source homogeneous data clustering for multi-target detection from cluttered background with misdetection

This paper investigates a particular data mining problem which is to ‘identify’ an unknown number of targets from noisy observations that are collected from multiple sources of unknown statistics, under possible misdetection.

Gespeichert in:
Autor*in:

Li, Tiancheng [verfasserIn]

De la Prieta Pintado, Fernando

Corchado, Juan M.

Bajo, Javier

Format:

E-Artikel

Sprache:

Englisch

Erschienen:

2017

Schlagwörter:

Constrained clustering

Multi-target detection

Sensor fusion

Object identification

Umfang:

11

Übergeordnetes Werk:

Enthalten in: Atomic collapse in graphene quantum dots in a magnetic field - Eren, I. ELSEVIER, 2022, the official journal of the World Federation on Soft Computing (WFSC), Amsterdam [u.a.]

Übergeordnetes Werk:

volume:60 ; year:2017 ; pages:436-446 ; extent:11

Links:

Volltext

DOI / URN:

10.1016/j.asoc.2017.07.012

Katalog-ID:

ELV040837122

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